[BioC] adjPval and qvalue

James W. MacDonald jmacdon at med.umich.edu
Tue Mar 21 15:21:41 CET 2006


sabrina.shao wrote:
> Hello, all
> I am confused by the adjPval from maanova and qvalue. I am not sure 
> after I use the matest , which one I should use if I want to take a look 
> at the FDR. Should I compute the q-values of these adjusted P-values or 
> just use the original p-values to compute the corresponding q-values. Or 
> I have some misunderstanding about q-values and adjusted pvalues. Thanks

I think you are confused. The matest() function doesn't compute adjusted 
p-values. It computes permuted p-values which is a different thing. 
Anyway, the example for adjPval() pretty much outlines the steps you 
should be taking:

data(paigen)
      paigen <- createData(paigen.raw, n.rep=2)
      model.noint.fix <- makeModel(data=paigen, 
formula=~Array+Dye+Spot+Strain+Diet)
      # F-test strain effect
      ## Not run:
      test.strain.fix <- matest(paigen, model.noint.fix, term="Strain", 
n.perm=100,
              shuffle.method="resid", test.method=rep(1,4))
      # make FDR adjusted P values
      test.strain.fix <- adjPval(test.strain.fix)
      ## End(Not run)
      # there will be new fields in test.strain.fix after this

Best,

Jim


> 
> Sabrina
> 
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> Bioconductor at stat.math.ethz.ch
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-- 
James W. MacDonald, M.S.
Biostatistician
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623


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